广义不确定系统的终端滑模控制

本文研究了线性广义不确定系统在满足匹配条件下的终端滑模控制的综合设计问题.利用变结构控制方法设计切换函数和终端滑模控制器,获得了在终端滑模控制下,闭环系统的模态在有限时间内到达平衡点的重要结果.克服了传统的变结构控制方法只能保证闭环系统的模态在平衡点渐近稳定,不能实现有限时间到达平衡点的缺点.举例说明了设计方法的合理性和有效性.     

离散多时滞广义不确定系统的变结构控制

研究了线性离散多时滞广义不确定系统的变结构控制的综合与设计问题.首先引入了一种新的受限系统等价分解形式,把所给的系统分解成两个低维的子系统:一个是不带控制项的差分系统;一个是带有控制项的差分系统.其次,根据上面的分解形式及离散时滞广义系统鲁棒稳定性的有关结果,设计了带有差分补偿器的切换函数,使得系统在准切换流形上的运动渐近稳定.然后在不确定项有界的条件下,设计了离散变结构控制律,使得在此控制律的作用下,系统从状态空间中任意一点出发的解的轨迹,于有限步内或者到达准切换流形,此后在准切换流形上渐近滑向原点;或者进入准切换流形的一个小邻域内,并稳定于原点邻域内的一个小的抖振.最后给出了数值例子以说明该综合设计方法的可行性与简便性.     

基于扰动补偿趋近律的非匹配离散广义准滑模控制

研究了非匹配不确定离散广义系统准滑模控制策略的综合问题.给出了具有前级状态向量的动态切换函数,使得系统能够在切换带内稳定.设计了两种带有扰动补偿的离散广义趋近律,消除了常规滑模控制策略中不确定项必须有界的限制,且不必满足匹配条件.给出了系统准滑动模态保持逐步穿越切换面的必要条件,减小了准滑动模态切换带的带宽.所设计的滑模控制器在有限时间内可达切换面,削弱了系统抖振,有效地改善了系统动态品质.最后,数值算例验证了该控制策略的可行性.     

一类不确定离散混杂系统的稳定性

基于切换Lyapunov函数描述了在离散时间下一类不确定的离散混杂系统的L2增益分析以及控制合成问题.运用Lyapunov函数理论以及线性矩阵不等式,给出了一类不确定离散切换系统在任意切换律下的稳定性条件,并构造了反馈控制律使系统达到干扰衰减及内稳定性.     

基于RBF神经网络的鲁棒因子滑模变结构多自由度机械臂精确跟踪控制研究

针对具有时变干扰的不确定多自由度机械臂,文章设计了基于RBF神经网络的含有鲁棒因子的滑模变结构高精度跟踪控制方法.针对时变干扰,设计鲁棒因子,将其嵌入滑模变结构控制器,克服了时变干扰对系统跟踪性能的影响.将RBF神经网络控制算法结合鲁棒因子滑模变结构控制,估计多自由度机械手臂系统的不确定因素.采用Lyapunov函数方法,证明了系统的稳定性.对比分析了计算力矩法滑模变结构控制方法,仿真结果证明,基于RBF神经网络的鲁棒因子滑模控制,针对具有时变干扰的含有不确定因素的多自由度机械手臂系统,具有较为精确的跟踪性能.     

任意切换线性系统的鲁棒镇定及其DC-DC变换器切换控制

针对具有任意切换序列的不确定线性切换系统,提出一种鲁棒镇定切换控制律设计方法.通过求解一组线性矩阵不等式,计算切换系统的共同鲁棒控制Lyapunov函数,进而构造一个双自由度的切换状态反馈控制律.应用共同鲁棒控制Lyapunov函数性质和切换控制理论,证明所提切换控制律的鲁棒渐近稳定性和逆最优性及共同鲁棒扇形裕度(0.5,∞).最后以DC-DC升压变换器切换控制为例,仿真验证文章方法的有效性和实用性.     

一类不确定分数阶多混沌系统的终端滑模同步控制

根据分数阶系统理论利用终端滑模方法研究了分数阶不确定多混沌系统同步问题,获得了整数阶分数阶两种情形下多混沌系统取得滑模同步的充分性条件,最终结论说明设计合适的控制律和切换函数,分数阶多混沌系统取得滑模同步.     

具有饱和输入和非严格反馈结构的切换非线性系统的自适应模糊控制

针对一类具有非光滑饱和输入和非严格反馈结构的任意切换规则下的非线性切换系统,给出了一种模糊减少计算量控制算法.通过构造公共Lyapunov函数,利用模糊系统对非严格反馈结构和未知不确定函数进行建模,采用辅助函数补偿饱和输入问题,基于逼近最优估计参数的界以减少在线自适应调节参数数目.该控制算法在任意切换规则下不仅可以调节输入饱和不确定性,还可以减少自适应调节参数.基于Lyapunov稳定性理论证明闭环系统的所有信号是有界的.数值仿真结果可以有效地验证控制器和自适应律设计算法的可行性.     

具外部扰动的变时滞不确定奇异系统的滑动模态控制

研究了含有多个变时滞的不确定奇异系统的滑动模态问题.该系统相比文献中已研究的系统更为复杂,具有多个变时滞,且分别含有匹配和不匹配的外部扰动项.通过对系统进行等价分解化为两个子系统,对分解后的系统进行切换函数的设计,再通过定义Lyapunov函数得到使得系统的滑模运动渐近稳定的充分条件.由此证明了所设计的滑模控制率能够保证状态轨迹在优先时间内被驱动到指定的切换面上且保持运动.设计过程简单,且结果以线性矩阵不等式呈现,相比文献中已有的结论更易于实现.最后通过例子验证结论的正确性.     

若干类时滞切换系统的稳定性问题

主要研究了镇定切换系统的鲁棒稳定性问题.用切换lyapunov函数方法,通过定义指标函数,讨论了基于切换lyapunov函数的若干类时滞切换系统的稳定性问题,用矩阵不等式研究了时滞,时滞摄动和不确定时滞的切换系统的鲁棒稳定性.     

Adaptive fuzzy sliding mode control scheme for uncertain systems

Most physical systems inherently contain nonlinearities which are commonly unknown to the system designer. Therefore, in modeling and analysis of such dynamic systems, one needs to handle unknown nonlinearities and/or uncertain parameters. This paper proposes a new adaptive tracking fuzzy sliding mode controller for a class of nonlinear systems in the presence of uncertainties and external disturbances. The main contribution of the proposed method is that the structure of the controlled system is partially unknown and does not require the bounds of uncertainty and disturbance of the system to be known; meanwhile, the chattering phenomenon that frequently appears in the conventional variable structure systems is also eliminated without deteriorating the system robustness. The performance of the proposed approach is evaluated for two well-known benchmark problems. The simulation results illustrate the effectiveness of our proposed controller.     

基于随机模糊参数预测烧结法氧化铝生产中碱液成分

针对来自许多实际过程中数据变化的多态不确定性,提出一类新的预测方法。为了反映数据的多态不确定性,设计了一种分段推断算法来对样本数据的分布函数进行推断,在假设总体服从一类模糊随机变量的条件下,由该方法得到总体的分布函数的解析式。基于这种预测方法,对烧结法氧化铝生产过程中碱液成分进行了预测。预测结果表明新方法具有广泛的应用价值。     

Control of a novel class of fractional-order chaotic systems via adaptive sliding mode control approach

In this paper, an adaptive sliding mode controller for a novel class of fractional-order chaotic systems with uncertainty and external disturbance is proposed to realize chaos control. The bounds of the uncertainty and external disturbance are assumed to be unknown. Appropriate adaptive laws are designed to tackle the uncertainty and external disturbance. In the adaptive sliding mode control (ASMC) strategy, fractional-order derivative is introduced to obtain a novel sliding surface. The adaptive sliding mode controller is shown to guarantee asymptotical stability of the considered fractional-order chaotic systems in the presence of uncertainty and external disturbance. Some numerical simulations demonstrate the effectiveness of the proposed ASMC scheme.     

普适双变量随机气候模式的研究

该文对海气耦合双变量随机气候模式进行了系统研究，研究结果表明：（1）无论是考虑只有大气子系统的随机作用还是同时考虑大气子系统和海洋子系统的双扰动，对给定的扰动频率，海气气候系统对大气的扰动作用相当于一个十分简单的线性放大器；对于不同的扰动频率，在能量上海温的变化将随大气的扰动做4次幂的非线性响应;（2）若同时考虑大气子系统和海洋子系统的随机扰动，在满足细致平衡条件下可以求出系统定态的概率分布。否则，只有当扰动为弱噪声时，才能用级数展开法近似求出系统的概率分布。     

Adaptive synchronization for a unified chaotic system with uncertainty

A new adaptive controller is designed to synchronize of a unified chaotic system with uncertainty (unknown parameter, noise perturbation, etc.). It is implemented by using variable structure control. The controller designed here only uses the derivative information of the uncertainty. Even if the uncertainty is time-varying or unbounded, as long as its derivative is bounded, the adaptive controller can guarantee the synchronization of the unified chaotic system with uncertainty. Finally, digital simulation is carried out for Lorenz system, and the results verify the effectiveness of the proposed method.     

最速反馈控制的不变性

变结构控制对系统模型和扰动具有一定的不变性是众所周知的事实。最速反馈控制是以其开关曲线为滑动曲线的变结构控制。本文用变结构控制理论来讨论修正了的最速反馈控制对一定范围的系统扰动具有完全的不变性,即完全能够抑制一定范围的扰动作用,而且闭环系统的所有轨线,在理论上,都以有限时间到达原点。这就为设计高效非线性反馈提供了一条有效途径,还给出了避免高频颤震来实现最速反馈控制的数字化办法。     

Disturbance rejection in robust PdE-based MRAC laws for uncertain heterogeneous multiagent networks under boundary reference

Disturbance is a pervasive source of uncertainty in most applications. This paper presents model reference adaptive control (MRAC) laws for uncertain multiagent networks with a disturbance rejection capability. The algorithms proposed can also be viewed as the extension of the robust model reference adaptive control (MRAC) laws with disturbance rejection recently derived for systems described by parabolic and hyperbolic partial differential equations (PDEs) with spatially-varying parameters under distributed sensing and actuation to heterogeneous multiagent networks characterized by parameter uncertainty. The latter extension is carried out using partial difference equations (PdEs) on graphs that preserve parabolic and hyperbolic like cumulative network behavior. Unlike in the PDE case, only boundary input is specified for the reference model. The algorithms proposed directly incorporate this boundary reference input into the reference PdE to generate the distributed admissible reference evolution profile followed by the agents. The agent evolution thus depends only on the interaction with the adjacent agents, making the system fully decentralized. Numerical examples are presented as well. The resulting PdE MRAC laws inherit the robust linear structure of their PDE counterparts.     

Decision making under uncertainty comprising complete ignorance and probability

This paper investigates a model of decision making under uncertainty comprising opposite epistemic states of complete ignorance and probability. In the first part, a new utility theory under complete ignorance is developed that combines Hurwicz–Arrow's theory of decision under ignorance with Anscombe–Aumann's idea of reversibility and monotonicity used to characterize subjective probability. The main result is a representation theorem for preference under ignorance by a particular one-parameter function – the τ-anchor utility function. In the second part, we study decision making under uncertainty comprising an ignorant variable and a probabilistic variable. We show that even if the variables are independent, they are not reversible in Anscombe–Aumann's sense. This insight leads to the development of a new proposal for decision under uncertainty represented by a preference relation that satisfies the weak order and monotonicity assumptions but rejects the reversibility assumption. A distinctive feature of the new proposal is that the certainty equivalent of a mapping from the state space of uncertain variables to the prize space depends on the order in which the variables are revealed. Explicit modeling of the order of variables explains some of the puzzles in multiple-prior model and the models for decision making with Dempster–Shafer belief function.     

Nonlinear and chaos control of a micro-electro-mechanical system by using second-order fast terminal sliding mode control

In this paper, a novel second-order fast terminal sliding mode control (SFTSMC) scheme is proposed to suppress the chaotic motion of a micro-mechanical resonator with system uncertainty and external disturbance. To obtain a better disturbance rejection property, a fuzzy logic system is introduced to estimate the upper boundary of the sum of system uncertainty and external disturbance. Moreover, we employ the finite-time technique to obtain the properties of fast response and high precision. Finally, numerical simulations demonstrate the effectiveness of the proposed control scheme.